Activity
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Thanks to Matt Levine for getting the true story out about my article!
Thanks to Matt Levine for getting the true story out about my article!
Liked by Lore Dirick
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🌍 BelCham in Belgium 🇧🇪 Exciting news! Our Member Manager, Anton Wouters, will be traveling to Belgium for our BelCham Reception at KU Leuven on…
🌍 BelCham in Belgium 🇧🇪 Exciting news! Our Member Manager, Anton Wouters, will be traveling to Belgium for our BelCham Reception at KU Leuven on…
Liked by Lore Dirick
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𝟒𝟎 𝐘𝐞𝐚𝐫𝐬 𝐨𝐟 𝐂𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬, 𝐏𝐚𝐲𝐢𝐧𝐠 𝐈𝐭 𝐅𝐨𝐫𝐰𝐚𝐫𝐝, 𝐚𝐧𝐝 𝐌𝐚𝐤𝐢𝐧𝐠 𝐖𝐚𝐯𝐞𝐬: 𝟒𝟎 𝐘𝐞𝐚𝐫𝐬…
𝟒𝟎 𝐘𝐞𝐚𝐫𝐬 𝐨𝐟 𝐂𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬, 𝐏𝐚𝐲𝐢𝐧𝐠 𝐈𝐭 𝐅𝐨𝐫𝐰𝐚𝐫𝐝, 𝐚𝐧𝐝 𝐌𝐚𝐤𝐢𝐧𝐠 𝐖𝐚𝐯𝐞𝐬: 𝟒𝟎 𝐘𝐞𝐚𝐫𝐬…
Liked by Lore Dirick
Experience & Education
Licenses & Certifications
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Data Analysis in R, the data.table Way
DataCamp
Credential ID 78ba2004b2628cf172a6e59dc8cbc884e97ea00b -
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Publications
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Time to default in credit scoring using survival analysis: a benchmark study
Journal of the Operational Research Society
We investigate the performance of various survival analysis techniques applied to ten actual credit data sets from Belgian and UK financial institutions. In the comparison we consider classical survival analysis techniques, namely the accelerated failure time models and Cox proportional hazards regression models, as well as Cox proportional hazards regression models with splines in the hazard function. Mixture cure models for single and multiple events were more recently introduced in the…
We investigate the performance of various survival analysis techniques applied to ten actual credit data sets from Belgian and UK financial institutions. In the comparison we consider classical survival analysis techniques, namely the accelerated failure time models and Cox proportional hazards regression models, as well as Cox proportional hazards regression models with splines in the hazard function. Mixture cure models for single and multiple events were more recently introduced in the credit risk context. The performance of these models is evaluated using both a statistical evaluation and an economic approach through the use of annuity theory. It is found that spline-based methods and the single event mixture cure model perform well in the credit risk context.
Other authorsSee publication -
Macro-economic factors in credit risk calculations: including time-varying covariates in mixture cure models
Journal of Business & Economic Statistics
The prediction of the time of default in a credit risk setting via survival analysis needs to take a high censoring rate into account. This rate is due to the fact that default does not occur for the majority of debtors. Mixture cure models allow the part of the loan population that is unsusceptible to default to be modelled, distinct from time of default for the susceptible population. In this paper, we extend the mixture cure model to include time-varying covariates. We illustrate the method…
The prediction of the time of default in a credit risk setting via survival analysis needs to take a high censoring rate into account. This rate is due to the fact that default does not occur for the majority of debtors. Mixture cure models allow the part of the loan population that is unsusceptible to default to be modelled, distinct from time of default for the susceptible population. In this paper, we extend the mixture cure model to include time-varying covariates. We illustrate the method via simulations and by incorporating macro-economic factors as predictors for an actual bank data set.
Other authorsSee publication -
An Akaike information criterion for multiple event mixture cure models
European Journal of Operational Research
In this paper, we derive a form of the Akaike information criterion for variable selection for mixture cure models, which are often fit via the expectation–maximization algorithm. Separate covariate sets may be used in the mixture components. The selection criteria are applicable to survival models for right-censored data with multiple competing risks and allow for the presence of a non-susceptible group. The method is illustrated on credit loan data, with pre-payment and default as events and…
In this paper, we derive a form of the Akaike information criterion for variable selection for mixture cure models, which are often fit via the expectation–maximization algorithm. Separate covariate sets may be used in the mixture components. The selection criteria are applicable to survival models for right-censored data with multiple competing risks and allow for the presence of a non-susceptible group. The method is illustrated on credit loan data, with pre-payment and default as events and maturity as the non-susceptible case and is used in a simulation study.
Other authors
Honors & Awards
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Prince Albert Fund Grantee 2016
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The Prince Albert Fund helps young talented Belgian professionals acquire experience in conducting international projects. For more information, see http://www.princealbertfund.be/
Languages
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English
Full professional proficiency
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Dutch
Native or bilingual proficiency
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French
Professional working proficiency
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Italian
Limited working proficiency
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German
Elementary proficiency
More activity by Lore
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Impressive speaker lineup at #DataCitizens '24 on the Road in #NewYork on October 10th! Interested in how transforming and governing data impacts…
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Is Belgium ready to scale up its energy networks for a sustainable future? 🇧🇪⚡ That is one of the key questions tackled yesterday at the Boston…
Is Belgium ready to scale up its energy networks for a sustainable future? 🇧🇪⚡ That is one of the key questions tackled yesterday at the Boston…
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I agree with Harry. Early stage venture has become entirely too complicated. While I agree with him, I also don’t think it will change and here’s…
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Before saying my final goodbye and returning to Belgium, it´s nice to take a moment to reflect and appreciate what we have already achieved at…
Before saying my final goodbye and returning to Belgium, it´s nice to take a moment to reflect and appreciate what we have already achieved at…
Liked by Lore Dirick
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